A Guide to Applied Systems Engineering (ASE) is a practical, hands-on introduction to system design. It examines the multidisciplinary processes involved in system design, including modeling and simulation, optimization methods, and risk management tools. It also discusses the benefits and limitations of applying ASE to real-world situations. This article is for people interested in learning more about this emerging discipline. ASE is an integral part of the engineering process for organizations, governments, and military forces.
Multidisciplinary Effort
Systems engineering can be applied to complex systems, such as spacecraft. It has been used to design anything from refrigerators to the Space Shuttle Transportation System. The discipline evolved as a means to decrease development time and risk and to improve product quality. The following are some of the reasons systems engineering is a valuable tool in the design process. A successful system requires a team of engineers with diverse backgrounds and experience. Keeping this in mind, it is essential to consider the needs of each unit.
Concurrent engineering is one of the keys to a successful outcome. Unlike the traditional engineering process, in which subsystems are designed differently, contemporary engineering allows for rapid concept evolution. In addition to avoiding costly rework, concurrent engineering reduces costs. Design changes at later stages are expensive, and locking in too early can cause problems and poor performance. However, contemporary engineering is not for every project. Consider how your current process might impact a future project.
Modeling and Simulation
System-level simulations are crucial for predicting future events and improving designs. Simulations can represent a variety of systems, including physical and electronic ones.
In addition to providing data for design evaluation, modeling and simulation are often used to support system acquisitions within government organizations. Using M&S helps to explore the design trade-offs, gain confidence that the system will perform as expected, and troubleshoot problems during the implementation stage. It also helps engineers document lessons learned and archive them. A model’s results can only be as good as its underlying assumptions, conceptualizations, and constraints. M&S is particularly interested in models that support executable versions on a computer. Furthermore, it can be updated to incorporate results from real-world experiments.
M&S should be integrated into a system’s life cycle to be most effective and support all phases of systems engineering. There are three classes of models and simulations: live, constructive, and virtual. In addition, model confidence can be established through formal validation and verification. Integrated engineering teams should be involved in M&S planning as early as possible. In addition, planning should include M&S activities and be proactive, early, and continuous.
Optimization Methods
Applied Systems Engineering is a field in which engineering design and optimization methods are combined to address a particular problem. In this area, effectiveness measures are the aspects of the problem that will be evaluated and included in system optimization and trade-off studies. In addition, the allocation of requirements sets the constraints on the design process. Thus, optimal system design is a constrained optimization problem.
Calculus-based optimization methods seek to find the minimum value of continuous or differentiable functions. They utilize sensitivity information to build local models of the constraint and objective functions. A sequence of updates to these models solves the more significant optimization problem. When local minima are reached, the search procedure stops. This is a foundation for more sophisticated optimization techniques.
